Senior Data Engineer

Senior Data Engineer

Key Responsibilities

1. Design, build, and maintain scalable ETL/ELT pipelines that move data reliably from source systems into the warehouse.

2. Own the architecture and performance of the data warehouse (BigQuery, Snowflake, or similar), including schema design, partitioning, and query optimization.

3. Build and maintain data infrastructure using modern orchestration tools (Airflow, dbt, or similar), ensuring pipelines are automated, monitored, and self-healing where possible.

4. Partner with Analysts to define standardized metrics, enforce data quality checks, and establish company-wide data governance practices.

5. Continuously evaluate and improve system performance, cost-efficiency, and scalability as data volume and complexity grow.

6. Peer-review the work of junior engineers, establish engineering best practices, and champion clean, well-documented, reproducible code.

Requirements

1. 5–7+ years in a data engineering or backend infrastructure role.

2. Expert-level SQL and strong proficiency in Python (or Scala/Java); deep experience with ETL/ELT frameworks.

3. Strong understanding of distributed systems, data modeling, and pipeline orchestration (Airflow, dbt, Prefect, or similar).

4. Expert knowledge of cloud data warehouse environments (BigQuery, Snowflake, Redshift) and cloud platforms (AWS, GCP, or Azure).

5. Ability to translate infrastructure decisions and trade-offs into clear implications for the wider data team and business stakeholders.

<